Update README.md

README.md

@@ -28,76 +28,192 @@ metrics:
 library_name: transformers
 ---
 
-# ALBERTI
-
-ALBERTI is a set of two BERT-based multilingual model for poetry. One for verses and another one for stanzas. This model has been further trained with the PULPO corpus for verses using [Flax](https://github.com/google/flax), including training scripts.
-
-See https://arxiv.org/abs/2307.01387.
-
-This is part of the
-[Flax/Jax Community Week](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104), organised by [HuggingFace](https://huggingface.co/) and TPU usage sponsored by Google.
-
-## PULPO
-
-PULPO, the Prolific Unannotated Literary Poetry Corpus, is a set of multilingual corpora of verses and stanzas with over 72M words.
-
-The following corpora has been downloaded using the [Averell](https://github.com/linhd-postdata/averell/) tool, developed by the [POSTDATA](https://postdata.linhd.uned.es/) team:
-
-### Spanish
-- [Disco v3](https://github.com/pruizf/disco)
-- [Corpus of Spanish Golden-Age Sonnets](https://github.com/bncolorado/CorpusSonetosSigloDeOro)
-- [Corpus general de poesía lírica castellana del Siglo de Oro](https://github.com/bncolorado/CorpusGeneralPoesiaLiricaCastellanaDelSigloDeOro)
-- [Gongocorpus](https://github.com/linhd-postdata/gongocorpus) - [source](http://obvil.sorbonne-universite.site/corpus/gongora/gongora_obra-poetica)
-### English
-- [Eighteenth-Century Poetry Archive (ECPA)](https://github.com/alhuber1502/ECPA)
-- [For better for verse](https://github.com/waynegraham/for_better_for_verse)
-### French
-- [Métrique en Ligne](https://crisco2.unicaen.fr/verlaine/index.php?navigation=accueil) - [source](https://github.com/linhd-postdata/metrique-en-ligne)
-### Italian
-- [Biblioteca italiana](https://github.com/linhd-postdata/biblioteca_italiana) - [source](http://www.bibliotecaitaliana.it/)
-### Czech
-- [Corpus of Czech Verse](https://github.com/versotym/corpusCzechVerse)
-### Portuguese
-- [Stichotheque](https://gitlab.com/stichotheque/stichotheque-pt)
-
-Also, we obtained the following corpora from these sources:
-### Spanish 
-- [Poesi.as](https://github.com/linhd-postdata/poesi.as) - [source](http://www.poesi.as/)
-### English
-- [A Gutenberg Poetry Corpus](https://github.com/aparrish/gutenberg-poetry-corpus)
-### Arabic
-- [Arabic Poetry dataset](https://www.kaggle.com/ahmedabelal/arabic-poetry)
-### Chinese
-- [THU Chinese Classical Poetry Corpus](https://github.com/THUNLP-AIPoet/Datasets/tree/master/CCPC)
-### Finnish
-- [SKVR](https://github.com/sks190/SKVR)
-### German
-- [TextGrid Poetry Corpus](https://github.com/linhd-postdata/textgrid-poetry) - [source](https://textgrid.de/en/digitale-bibliothek)
-- [German Rhyme Corpus](https://github.com/tnhaider/german-rhyme-corpus)
-### Hungarian
-- [verskorpusz](https://github.com/ELTE-DH/verskorpusz)
-### Portuguese
-- [Poems in Portuguese](https://www.kaggle.com/oliveirasp6/poems-in-portuguese)
-### Russian
-- [19 000 Russian poems](https://www.kaggle.com/grafstor/19-000-russian-poems)
-
-## Team members
-
-- Álvaro Pérez ([alvp](https://huggingface.co/alvp))
-- Javier de la Rosa ([versae](https://huggingface.co/versae))
-- Aitor Díaz ([aitordiaz](https://huggingface.co/aitordiaz))
-- Elena González-Blanco
-- Salvador Ros ([salva](https://huggingface.co/salva))
-
-## Useful links
-
-- [Community Week timeline](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104#summary-timeline-calendar-6)
-- [Community Week README](https://github.com/huggingface/transformers/blob/master/examples/research_projects/jax-projects/README.md)
-- [Community Week thread](https://discuss.huggingface.co/t/bertin-pretrain-roberta-large-from-scratch-in-spanish/7125)
-- [Community Week channel](https://discord.com/channels/858019234139602994/859113060068229190)
-- [Masked Language Modelling example scripts](https://github.com/huggingface/transformers/tree/master/examples/flax/language-modeling)
-- [Model Repository](https://huggingface.co/flax-community/alberti-bert-base-multilingual-cased/)
-
-## Acknowledgments
-
-This project would not have been possible without the infrastructure and resources provided by HuggingFace and Google Cloud. Moreover, we want to thank POSTDATA Project (ERC-StG-679528) and the Computational Literary Studies Infrastructure (CLS INFRA No. 101004984) of the European Union's Horizon 2020 research and innovation programme for their support and time allowance.
+# Model Card for Aʟʙᴇʀᴛɪ:
+Aʟʙᴇʀᴛɪ is the first multilingual domain-specific language model for poetry analysis.
+
+## Model Details
+
+### Model Description
+
+As a pre-trained language model, it is trained using the masked language modeling objective on top of [multilingual BERT](https://huggingface.co/bert-base-multilingual-cased), and therefore **it needs to be fine-tuned to specific tasks**.
+
+- **Developed by:** [Javier de la Rosa](https://huggingface.co/versae), and [Álvaro Pérez Pozo](https://huggingface.co/)
+- **Shared by:** [Javier de la Rosa](https://huggingface.co/versae)
+- **Model type:** `bert`
+- **Language(s) (NLP):** Spanish, French, Italian, Czech, Portuguese, English, Arabic, Finnish, German, Russian, Hungarian, Chinese.
+- **License:** [CC-BY 4.0](https://creativecommons.org/licenses/by/4.0/)
+- **Finetuned from model:** [https://huggingface.co/bert-base-multilingual-cased](bert-base-multilingual-cased)
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Paper:** https://arxiv.org/abs/2307.01387
+- **Demo:** https://huggingface.co/spaces/linhd-postdata/alberti
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure 
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Data Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+
+